Investigating functional brain networks and patterns using sparse representation of fMRI
data has received significant interests in the neuroimaging community. It has been reported …

Multimodal neuroimaging provides a rich source of data for identifying brain regions
associated with disease progression and aging. However, present studies still typically …

Recent studies have shown that resting-state spontaneous brain activity unveils intrinsic
cerebral functioning and complete information brought by prototype task study. From these …

Classification of brain states obtained through functional magnetic resonance imaging
(fMRI) poses a serious challenges for neuroimaging community to uncover discriminating …

In this paper, we focus on how to locate the relevant or discriminative brain regions related
with external stimulus or certain mental decease, which is also called support identification …

Functional behavior of the brain can be captured using functional Magnetic Resonance
Imaging (fMRI). Even though fMRI signals have temporal and spatial structures, most studies …

Interior point methods (IPMs) constitute one of the most important classes of optimization
methods, due to their unparalleled robustness, as well as their generality. It is well known …

Feature selection is an important topic of pattern recognition for enhancing classification and
potential biomarker discovery in medical image analysis. However, traditional multivariate …

We study the convergence of the ADMM (Alternating Direction Method of Multipliers)
algorithm on a broad range of penalized regression problems including the Lasso, Group …

State-of-the-art approaches in Schizophrenia research investigate neuroanatomical
biomarkers using structural Magnetic Resonance Imaging. However, current models are 1) …